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perpetua

FM Head Researchers
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Issue Comments posted by perpetua

  1. Club income doesn't rely on social media followers or shirt sale numbers in the game.  We actually define clubs' commercial income in the database and the game uses this, rather than using social media followers and shirt sales to calculate club income.

    The game coders appear to have used some estimation method for social media followers and shirt sales which unfortunately doesn't yield realistic results for Turkish clubs since our clubs are structured differently than most European/English clubs.  

  2. 5 hours ago, nympetamin said:

    Since the raters can give limited points, they may be missing some points deliberately. Someone who passes the players by turning agile, usually when the player receives the ball. This is one of the most distinctive features. A different scout will probably give a value between 14 and 16. @Perpetua'

    It's a matter of opinion.  

    It's possible for a researcher to want to better reflect a player's strengths so they have to look for players' weaknesses.  Sometimes strengths are too strong and weaknesses are too weak.  Sometimes strengths are too weak while weaknesses are too strong.  I'm sure the Fenerbahce researcher will take on board the comments and make amendments if he deems necessary.

  3. Yeah there seems to have been a mixup with respect to job roles for Fenerbahce.  We'll get it sorted.

     

    We don't enter the number of social media followers in the database.  This is game generated and it seems the game is doing a poor job of it.  We're going to investigate.

  4. Looks like he has departed anyway.

    Also it seems that he has more of a role on the player agent side than the club side.
    On the club side he seems to have positioned himself as a consultant, for which we don't really have a job in FM.
    We'll revisit adding him if he ends up working at a club in a defined role.

    Thanks!

  5. We also request you please adhere to the following three point plan when posting in the data topics:

    • State what you think is specifically wrong with a particular piece of data.              
    • State what you think the data should be.                            
    • State reasons/proof for your suggested corrections/improvements.   
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